System and methods for detecting, confirming, classifying, and monitoring a fire

ABSTRACT

One variation of a method for detecting a fire includes: during a first time period: detecting an increase in ambient light intensity and detecting an increase in ambient humidity; responsive to the increase in ambient light intensity and the increase in ambient humidity, detecting a fire event; during a second time period: correlating a decrease in ambient light intensity with an increase in visual obscuration; detecting an increase in ambient air temperature; in response to a magnitude of the increase in visual obscuration remaining below a high obscuration threshold and a magnitude of the increase in ambient temperature remaining below a high temperature threshold, classifying the fire as an incipient fire; and, in response to the magnitude of the increase in visual obscuration exceeding the high obscuration threshold and the magnitude of the increase in ambient temperature exceeding the high temperature threshold, classifying the fire as a developed fire.

CROSS-REFERENCE TO RELATED APPLICATIONS

This Application is a continuation application of U.S. patentapplication Ser. No. 17/481,185, filed on 21 Sep. 2021, which is acontinuation application of U.S. patent application Ser. No. 16/925,858,filed on 10 Jul. 2020, which is a continuation application of U.S.patent application Ser. No. 16/456,310, filed on 28 Jun. 2019, which isa continuation application of U.S. patent application Ser. No.15/985,666, filed on 21 May 2018, which is a continuation application ofU.S. patent application Ser. No. 15/374,781, filed on 9 Dec. 2016, whichclaims the benefit of U.S. Provisional Application No. 62/265,351, filedon 9 Dec. 2015, each of which is incorporated in its entirety by thisreference.

TECHNICAL FIELD

This invention relates generally to the field of fire detection and morespecifically to a new and useful system and method for detecting,confirming, classifying, and monitoring a fire in the field of firedetection.

BRIEF DESCRIPTION OF THE FIGURES

FIG. 1 is a flowchart representation of a method;

FIG. 2 is a flowchart representation of one variation of the method;

FIG. 3 is a schematic representation of a system;

FIG. 4 is a flowchart representation of one variation of the method;

FIG. 5 is a graphical representation of one variation of the method;

FIG. 6 is a flowchart representation of one variation of the method; and

FIG. 7 is a flowchart representation of one variation of the method.

DESCRIPTION OF THE EMBODIMENTS

The following description of embodiments of the invention is notintended to limit the invention to these embodiments but rather toenable a person skilled in the art to make and use this invention.Variations, configurations, implementations, example implementations,and examples described herein are optional and are not exclusive to thevariations, configurations, implementations, example implementations,and examples they describe. The invention described herein can includeany and all permutations of these variations, configurations,implementations, example implementations, and examples.

1. Methods

As shown in FIG. 1 , a method S100 for detecting a fire includes: duringa first time period, detecting an increase in ambient light intensity ata light sensor in Block S110 and detecting an increase in ambienthumidity in Block S112; based on the increase in ambient light intensityand the increase in ambient humidity during the first time period,detecting a fire event in Block S120; during a second time periodsucceeding the first time period, correlating a decrease in ambientlight intensity detected by the light sensor with an increase in visualobscuration of the light sensor in Block S130 and detecting an increasein ambient air temperature in Block S132; and classifying the fire asone of an incipient fire and a developed fire based on a magnitude ofthe increase in visual obscuration and a magnitude of the increase inlocal temperature in Block S140.

As shown in FIG. 2 , one variation of the method S100 includes: at alight sensor, detecting a change in ambient light intensity from aninitial intensity to a first intensity at a first time in Block S110,the first intensity exceeding the initial intensity by a threshold lightintensity; based on variations in detected local light intensityfollowing the first time remaining within a threshold variation[magnitude], associating the change in ambient light intensity with alighting change event in Block S142; and based on variations in detectedambient light intensity following the first time exceeding a thresholdvariation [magnitude], associating the change in local light intensitywith a fire event in Block S120.

As shown in FIG. 2 , another variation of the method S100 includes:correlating an increase in ambient light intensity within a space withpossibility of a fire event in Block S110; confirming the fire eventwithin the space based on an increase in ambient humidity in Block S112;transmitting an alarm to a fire alarm panel, a central station, and/orto an emergency responder in response to confirmation of the fire eventin Block S150; detecting a composition of gaseous combustion productswithin the space in Block S134; generating a protection equipmentspecification for the fire event based on the composition of gaseouscombustion products in Block S152; and transmitting the protectionequipment specification to the emergency responder in Block S154.

2. Applications

Generally, Blocks of the method S100 can be executed by an integratedfire detection system (the “system 100”) to rapidly detect a possiblefire event, to confirm the fire event, to classify the fire onceconfirmed, to monitor the fire over time, and to supply classificationand state data for the fire to an emergency responder. In particular,rather than relying (solely) on plume dynamics to carry smoke andproducts of combustion from a fire to the system 100, the system 100 canrapidly detect a possible fire event by monitoring outputs of multiplesensors—such as a light sensor and a humidity sensor—and correlatingchanges in such measured ambient conditions with a possible fire event.The system 100 can reduce Type I (“false positive”) errors by confirminga possible fire event determined from data collected by one sensor withdata collected by one or more other sensors within the system 100. Forexample, the system 100 can distinguish fires that warrant an alarm(e.g., incipient fires, developed fires, and smoldering fires) from bothnon-fire events and nuisance fires (e.g., steam from a teapot, heat froman electric heater, burnt toast, a cutting torch). Following a possibleor confirmed fire event, the system 100 can also fuse various data—suchas humidity, light intensity, temperature, gas concentration, and motiondata collected over time—to determine if the fire is smoldering,incipient, or developing and to monitor the size, position, rate ofchange, temperature, etc. of the fire over time. Furthermore, the system100 (or a remote computer system that receives sensor data from thesystem 100) can transform these fire classification, fire history, andfire trajectory data into prompts or guidance for one or morestakeholders (e.g., occupants, an emergency responder), such as aspecification for necessary or recommended safety equipment, evacuationguidance, or methods for handling the fire.

Furthermore, during periods of operation in which a fire is notdetected, the system 100 can monitor ambient conditions, such astemperature and humidity, and upload ambient condition data to a localheating and ventilation system (e.g., a thermostat) within the samebuilding; the heating and ventilation system can then modify the outputof a heating or cooling system within the building according to thesedata. During periods of operation during which a fire is not detected,the system 100 can also monitor motion local to the system 100 and canupload these motion data to a security system within the building; thesecurity system can then manipulate these motion data supplied by thesystem 100 to selectively activate or deactivate an alarm, a camera,etc.

3. Integrated Fire Detection System

As shown in FIG. 3 , Blocks of the method S100 can be executed locallyby an integrated fire detection system (the “system”) including multiplesensors.

In one implementation, the system 100 includes a light sensor noconfigured to detect incident electromagnetic radiation, such as in thevisible, IR, and/or UV spectrums. In one example, the system 100includes a full-spectrum light sensor configured to output an analogvalue corresponding to an intensity of incident light across thevisible, IR, and UV spectrums. In another example, the system 100includes an IR sensor that outputs a value corresponding to an intensityof incident infrared energy. In yet another example, the system 100includes an RGB light sensor that outputs values corresponding tointensity of discrete, narrow bands of light in the visible spectrum,such as around 640 nm, 532 nm, and 465 nm. The system 100 can alsoinclude a combination of two or more types of light sensors. The system100 can also include a light tube or light pipe aligned with an inputside of the light sensor and configured to direct ambient light into thelight sensor.

The system 100 can also include a motion sensor 120. For example, thesystem 100 can include a laser or infrared motion sensor. The system 100can additionally or alternatively include a distance sensor 122 (e.g.,an acoustic or sonar distance sensor); the system 100 can determine adistance between the system 100 and an adjacent surface from a singleoutput of the distance sensor and can compare outputs of the distancesensor over time to detect motion near the system 100. Furthermore, thesystem 100 can include a pressure sensor, a microphone (or other soundsensor), a heat flux sensor, a light wavelength sensor, and/or a heatcolor sensor, etc.

In this implementation, the system 100 can include a housing 130 of aheat-resistant material, and the motion sensor and the light tube can bearranged on or near an exterior surface of the housing. For example, thehousing can define a short cylindrical structure with mounting featureson a first end, and the motion sensor and the light tube can be arrangedacross the second end with their corresponding fields of view facingoutwardly from and substantially parallel to the axis of the housing.

The system 100 can include one or more gas sensors 140, such as one ormore sensors configured to detect concentrations of carbon monoxide(CO), carbon dioxide (CO₂), oxygen (O₂), propane, butane, benzene,sulfur hexafluoride (SF₆), and/or hydrogen (H₂) in ambient air aroundthe system 100. Similarly, the system 100 can include a humidity sensor150 configured to detect a concentration of water vapor (e.g., arelative humidity, an absolute humidity) in ambient air around thesystem 100. Furthermore, the system 100 can include a temperature sensor160, such as a thermocouple or a thermopile, configured to detectambient air temperature within the space. In this implementation, thehousing can define an internal cavity interposed between two superficialvents 132, and the gas sensor(s), humidity sensor, and temperaturesensor can be arranged within the internal housing.

The system 100 can include a wireless communication module 170 (e.g., aWi-Fi radio, a cellular communication module) configured to broadcastfire-related and environmental data to an emergency responder, abuilding alarm system, a building security system, and/or a buildingHVAC system. The system 100 can also include a processor that interfaceswith one or more of the foregoing sensors, implements methods andtechniques described herein to locally detect, confirm, classify, andmonitor a fire, and broadcasts alarm and sensor data via the wirelesscommunication module. The system 100 can be configured to receive powerfrom a building in which the system 100 is installed via a wired powerconnection, and the system 100 can include a back-up battery.Alternatively, the system 100 can include and can be powered exclusivelyby an internal battery.

In one variation, the system 100 includes multiple directional sensorsets oriented on or within the housing to collect directional (orregional) data from the space. For example, the housing can define anextruded hexagonal structure with one directional sensor set arrangedacross each of the 0°, 120°, and 240° faces of the housing, wherein eachdirectional sensor set includes a distance sensor and a light sensor. Inthis example, the distance and light sensors in each directional sensorset can define fields of view angled outwardly from correspondingsurfaces on the housing, such as at an angle of 45° from the axis of thehousing to maximize a detectable volume within the space and minimizeoverlap between sensible volume across the directional sensor sets. Thesystem 100 can thus: determine the distance between the 0°, 120°, and240° faces and (nearest) opposing surfaces within the space via thedistance sensors; for each light sensor, transform a detected lightintensity into a light intensity at a light source within the field ofview of a light sensor based on the corresponding distance to anopposing surface (as described below); and then triangulate the positionof a light source (e.g., a fire) within the space based on the“normalized” light intensities detected at each light sensor in order todetermine a more specific position or location of the light sourcewithin the space at any time. Similarly, in this variation, the system100 can track the position of a primary light source (e.g., a fire) ineach of three 120° tridrants within the space based on peak (normalized)changes in light intensity detected at each light sensor within thesystem 100. In this variation, the system 100 can implement methods andtechniques described herein for each sensor set (or for a compositesensor image containing data from each sensor set) to detect, confirm,classify, and/or monitor a fire in the field of view of each sensor set.

However, the system 100 can include any other combination of sensors ofany other suitable type and arranged on or within a housing of any othermaterial or geometry.

4. Setup

The system 100 can be installed within a structure, such as within aroom or hallway within an industrial, commercial, residential, ormized-use structure or within a ship, train, or other vehicle. Forexample, the system 100 can be installed on a ceiling or on a wall, suchas at a standard height of 48″ on a wall; as described below, the system100 can be configured to apply a fire detection and monitoring modelbased on its installed position. For example, a professional installercan: install the system 100 within a space; access a native system setupapplication executing on a tablet computer; enter or scan a UUID, serialnumber, bar code, or other identifier coded into or applied onto thesystem 100 into the native system setup application; and then enter aroom number, a position within the room, a distance between the sensorand an opposing surface (e.g., to a floor for a ceiling installation, toan opposing wall for a wall installation). The native system setupapplication can pass these system identifying data and installation datato a remote computer system; and the remote computer system can retrievea fire detection and monitoring model for the system 100 based on theseinstallation data and then route these data directly to the system 100via a cellular connection based on the system 100 identification data orindirectly through the tablet computer.

Alternatively, once installed, the system 100 can execute anauto-calibration routine to calibrate and/or select a fire detection andmonitoring model. In particular, because the intensity ofelectromagnetic radiation incident on the light sensor (or on the lighttube optically coupled to the light sensor) may be a function of theinverse square of the distance between the light sensor and a source ofthe electromagnetic radiation (i.e., 1/R², wherein R is the distancebetween the light sensor and the light source), the system 100 canautomatically determine its distance from an opposing surface and applythis distance to intensities of detected light in order to estimate abrightness or intensity of a source of the detected light. For example,once installed (and regularly after installation, such as once daily),the system 100 can sample the output of an integrated sonar- orlaser-based distance sensor to determine a distance to a nearest surfaceand can then store this distance as an approximate, single-valuecalibration distance (“R_(cal)”) for transforming the detected intensityof incident light (“I_(inc)”) into a light intensity at a light source(“I_(source)”) (e.g., according to the formulaI_(source)=c₁×I_(inc)×R_(cal) ²).

In the variation described above in which the system 100 includesmultiple directional sensor sets, the system 100 can implement theforegoing methods and techniques for each directional sensor set.However, the system 100 can be manually configured in any other way orcan automatically execute a configure routine to select and/or adjust afire detection and monitoring model for the system 100's particularinstallation.

The method S100 is described herein as executed locally by a single unitof the system 100. However, Blocks of the method S100 can be similarlyexecuted across a distributed network of multiple like units of thesystem 100, such as installed throughout a commercial building,residential building, ship, aircraft, or other structure. Blocks of themethod S100 can additionally or alternatively be executed by a centralcontroller (e.g., a local building management program) or a remotecomputer system (e.g., a remote server) in communication with units ofthe system 100 of other sensors distributed throughout the building orstructure.

5. Fire Detection and Confirmation

The system 100 executes Blocks of the method S100 to detect a possiblefire event based on data collected at a first sensor (e.g., the lightsensor) and then confirms the fire event based on data collectedsimultaneously or soon thereafter at one or more other sensors (e.g.,the humidity sensor) within the system 100. In particular, for a sensorin the system 100, the system 100 compares outputs of the sensor over aperiod of time (e.g., a period of several minutes) to identify changesin an ambient condition measured by the sensor. Then, based on amagnitude, rate, and/or frequency of a change in one or more ambientconditions, the system 100 can detect and/or confirm a fire event. Thesystem 100 can therefore track changes in one or more ambientconditions—rather than or in addition to absolute ambient conditionvalues—to detect, confirm, and classify a fire event over time (e.g.,such that the sensors need not be calibrated and/or reset over time dueto sensor creep).

Generally, as a fire ignites and then develops within a space, the firemay emit electromagnetic radiation (e.g., infrared light) that is firstregistered—at a first time—by the light sensor as an increase in lightintensity over a recent steady-state incident light intensity in BlockS110. Based on variations in the intensity of this electromagneticradiation following the detected increase, the system 100 can confirmthat the increased light intensity corresponds to a flame or fire, as inBlock S110 described above. With water as a product of combustion, therelative humidity within the space (e.g., a closed, confined space) mayinitially increase; as moisture from the flame moves within the spaceand reaches the system 100 at a second time, the humidity sensor canregister this increase in humidity over a recent steady-state humidityin Block S112, and the system 100 can apply this detected humidityincrease to the previously-detected increase in ambient light intensityto confirm presence of a fire within the space in Block S110. Therefore,in one implementation, the system 100 can detect and confirm a fireevent in Block S110 by first detecting an increase in ambient lightintensity in Block S110 followed by an increase in ambient humidity inBlock S112.

For example, the system 100 can detect a change in ambient lightintensity—via its integrated light sensor—from an initial intensity to afirst intensity at a first time. The system 100 can then set a fireevent flag—indicating that a possible fire event has occurred—atapproximately the first time if the first intensity exceeds the initialintensity by a threshold light intensity. The system 100 can then detectan increase in ambient humidity—via its integrated humidity sensor—fromthe first time to a second time; in response to such an increase inhumidity, the system can confirm the fire event flag as a fire event(i.e., confirm that a true fire event indicated by the fire event flaghas occurred).

The light sensor may exhibit a limited dynamic range and may thereforenot be able to detect both a change in light intensity from a relativelysmall fire at close range (e.g., a flame at a distance of 1 meterproducing less than 10 Watts of light) and a change in light intensityfrom a larger fire at a greater distance (e.g., a flame at a distance of3 meter producing less than 100 Watts of light). However, a small fire(or flame) may still release an amount of water vapor that changes thehumidity within the space by a magnitude within the dynamic range of thehumidity sensor. The system 100 can therefore initially detect such asmall fire based on a change in humidity within the space and can thenconfirm the fire as the flame grows to a size that is detectable by thelight sensor. For such small fires, the system 100 can additionally oralternatively detect changes in ambient gas constituents and/or anincrease in ambient temperature with the space and fuse these ambientchanges with the detected change in ambient humidity to confirm thepresence of a small fire (or flame) within the space.

Therefore, during normal operation, the system 100 can sample thehumidity sensor and the light sensor (and a limited subset of othersensors integrated into the system 100) and only begin to sample othersensors in the system 100—such as the gas sensor(s) and temperaturesensor—once a possible fire event is detected or only once a fire eventis confirmed. For example, during normal operation, the system 100: cansample the humidity sensor and the light sensor at a sampling rate of 1Hz for internal fire detection; and can sample the temperature sensor ata sampling rate of 0.1 Hz and upload temperature data with every tenthhumidity datum to a remote HVAC control system. In this example, once apossible fire event is detected or a fire event is confirmed by thesystem 100, the sensor can sample all samples within the system 100 at asampling rate of 1 Hz.

In another implementation, the system 100 can detect a possible fireevent based on a rapid change (e.g., a step-change) in ambient lightintensity and can then confirm or discard the possible fire event basedon variations in detected light intensity following the rapid ambientlight intensity change. In this implementation, the system 100 can: at alight sensor, detect a change in local light intensity from an initialintensity to a first intensity at a first time in Block S110, whereinthe first intensity exceeds the initial intensity by a threshold lightintensity; and, based on variations in detected local lightintensity—following the first time—remaining within a thresholdvariation, associating the change in local light intensity with alighting change event in Block S142. In particular, the system 100 canmap a rapid increase (e.g., a step-change increase) in ambient lightintensity followed by (near-) steady-state light intensity to activationof an electric light source (e.g., ceiling lights, a desk lamp) withinthe space. For example, if detected light fluxes over a period of 5seconds following the light intensity step change event remain within athreshold of +/−2.5% of the peak detected light flux at the lightintensity step change event, the system 100 can discard the lightintensity step change event as a possible fire event, reset a fire eventflag, and continue to search for a subsequent increase in lightintensity and/or humidity suggestive of a possible fire event, as inBlocks S110 and S112.

However, in the foregoing implementation, based on variations indetected local light intensity—following the light intensity step changeevent—exceeding a threshold variation, the system 100 can associate thechange in local light intensity with a fire event in Block S120. Inparticular, the light intensity from a burning fire may varysignificantly (e.g., by more than 5% in radiated power) on amulti-second time scale. The system 100 can therefore correlate a large,rapid change in light intensity (e.g., a near-step-change increase ofmore than 100% in detected light intensity) followed by significantvariations of detected light intensity (not characteristic of anelectric light source (e.g., varying at 60 Hz), sunlight, or movingcloud cover) with (rapid) onset of a fire. For example, the system 100can correlate the light intensity step change event with a possible fireevent and then confirm the fire event if detected light fluxes over aperiod of 5 seconds following the light intensity step change eventexceed a threshold of +/−2.5% of the peak detected light flux at thelight intensity step change event. The system 100 can thus directlycorrelate a rapid change in incident light intensity followed by afluctuation in incident light intensity as a fire event. Alternately,the system 100 can set a possible fire event flag based on a lightintensity step change followed by significant variations in incidentlight intensity and then confirm this fire event based on a change inanother measured ambient condition within the space, such as humidity ortemperature, as described above.

In one implementation, the system 100 can detect and confirm a fireevent based on an increase in ambient light intensity followed by adecrease in ambient light intensity. In particular, the onset of a firecan be accompanied by a significant increase in ambient light intensity,which the system 100 can detect via its integrated light sensor. As thefire burns and produces smoke, this smoke may obscure light produced bythe fire from reaching the light sensor, thereby yielding a decrease inambient light intensity detected by the system 100 as the fire burns.The system 100 can therefore associate a decrease in detected lightintensity—following an increase in detected light intensity and issuanceof a fire event flag—with an increasing presence of smoke (e.g., a highdensity of smoke near the system 100). For example, the system 100 can:detect a change in ambient light intensity—from a stream of data outputby the integrated light sensor—from an initial intensity to a firstintensity at a first time; and then set a fire event flag at a firsttime if the first intensity of ambient light exceeds the initialintensity by a threshold light intensity, as described above. Once thefire event flag is set, the system 100 can continue to track ambientlight intensity; if the system 100 then detects an increase in lightintensity from the first time to a second time followed by a decrease inlight intensity from the second time to a third time, the system 100 canconfirm the fire event flag as a fire event, as described above.

However, the system 100 can detect and confirm a fire event based ondetected changes in any other one or more ambient conditions over time.

6. False-Positive Rejection

The system 100 can implement similar methods and techniques describedabove to discard potential fire events as non-fire (or “nuisance alarm”)events based on changes in one or more ambient conditions following adetection of a possible fire event. For example, a hot tea kettle mayrelease steam that increases the ambient humidity within a space, butlack of a fire (or a growing fire) within the space may yield noincrease in the ambient light within the space; the system 100 candetect a possible fire event based on such a rise in ambient humiditybut then discard the possible fire event if no increase in ambient lightintensity (and/or if no other change in ambient gas constituents) isdetected, as shown in FIG. 5 . In another example, a heater may increasethe ambient temperature within a space but may not affect ambient lightintensity or humidity within the space; the system 100 can detect apossible fire event based on such a rise in ambient temperature but thendiscard the possible fire event if no increase in ambient lightintensity (and/or if no other change in ambient humidity or gasconstituents) is detected. However, in this example, the system 100 canupdate a baseline temperature over time as the heater heats the space.In another example, toast burning in a toaster may create smoke thatobscures the light sensor—which reduces light intensity detected by thelight sensor—and that contains gas constituents common to fire; thesystem 100 can detect a possible fire event based on such a change inlight intensity and gas constituents but then discard the possible fireevent if no increase in ambient humidity and/or temperature is detectedsoon thereafter.

In one implementation, the system 100 can discard a potential fire eventbased on a frequency of fluctuation in ambient light intensity.Generally, a burning fire may “flicker” at a rate between 1 Hz and 20Hz; smoke produced by the fire may also affect transmission of lightfrom the fire to the system 100, thereby yielding fluctuations indetected light intensity at the system 100. Therefore, if a globalincrease in ambient light intensity—for which the system 100 sets a fireevent flag—is accompanied by light intensity fluctuations outside ofthis range characteristic of a fire, the system 100 can determine thatthe increase in ambient light intensity was due to a change of state ofan innocuous light source and then discard the fire event flagaccordingly. For example, if the global increase in light intensity ischaracterized by light fluctuations in the range of 60 Hz in NorthAmerica (or 50 Hz in Europe), the system 100 can interpret this increasein ambient light intensity as stemming from an overhead light that wasswitched on and discard the fire event flag accordingly.

In the foregoing implementation, after detecting a change in ambientlight intensity to a first light intensity that exceeds a thresholdlight intensity at a first time, the system 100 can calculate afrequency of fluctuation in ambient light intensity at a second timefollowing the first time. In response to the frequency of fluctuation inambient light intensity remaining below a low frequency threshold (e.g.,1 Hz), the system 100 can associate the change in ambient light with alighting change event suggestive of innocuous ambient light (e.g.,sunlight). In response to the frequency of fluctuation in ambient lightexceeding the low frequency threshold and remaining above a highfrequency threshold (e.g., 40 Hz), the system 100 can associate thechange in ambient light with a lighting change event suggestive ofactivation of artificial lighting (e.g., a fluorescent light beingswitched on). In response to the frequency of fluctuation in ambientlight falling between the low frequency threshold and the high frequencythreshold, the system 100 can associate the change in ambient light withan active fire and confirm the fire event flag as a fire eventaccordingly. The system 100 can thus monitor a possible fire event overtime and confirm or discard a fire event flag for the possible fireevent as a function of a frequency of fluctuation in detected ambientlight intensity.

The system 100 can therefore compare changes across multiple ambientconditions and discard or confirm a fire event accordingly.

7. Fire Classification

Once the fire event is confirmed, the system 100 can map point andtime-based data output from the light, humidity, temperature, gas,and/or other internal sensors to a classification of the fire, such asone of a smoldering fire classification, an incipient fireclassification, and a developed fire classification, as shown in FIG. 2.

Generally, as the fire continues to burn the intensity ofelectromagnetic radiation detected by the light sensor may increase fromthe first time as the fire develops but then decrease as either A) thefire dies or B) smoke from the fire (e.g., a developing or incipientfire) fills space around the system 100 and obscures the light sensor.To distinguish a dying fire from a developing or incipient fire, thesystem 100 can sample the temperature sensor and then: correlate aminimal temperature increase (e.g., less 10° F. increase) from adetected temperature at the first time with a smoldering (e.g., dying)fire; correlate a moderate temperature increase (e.g., between of 10° F.and 30° F.) from the detected temperature at the first time with anincipient fire; and correlate a large temperature increase (e.g.,greater than 30° F.) from the detected temperature at the first timewith a developing fire, as shown in FIG. 5 . The system 100 can confirmthese temperature-based smoldering, incipient, and developing fireclassifications based on a magnitude of motion detected by the motionsensor. For example, the system 100 can: confirm that the fire issmoldering if an output of the motion sensor indicates minimal localmotion (e.g., less than one output state change at the motion sensor perten-second interval at a sampling rate of 1 Hz); confirm that the fireis incipient if an output of the motion sensor indicates moderate localmotion (e.g., between two and five output state changes at the motionsensor per ten-second interval at a sampling rate of 1 Hz); and confirmthat the fire is developing if an output of the motion sensor indicatesa high rate of local motion (e.g., more than five output state changesat the motion sensor per ten-second interval at a sampling rate of 1Hz), as shown in FIG. 5 .

In one implementation, following confirmation of a fire event (e.g.,based on an increase in ambient light intensity, a frequency offluctuation in ambient light intensity, and a change in humidity,temperature, etc.), the system 100 can monitor various parameters of thefire event (e.g., humidity, temperature, etc.) over time and classify astate of the fire based on changes in the parameters. In thisimplementation, after detecting a change in ambient light intensity froman initial intensity at an initial time to a first intensity at a firsttime, wherein the first intensity exceeds the initial intensity by athreshold intensity indicating a possible fire event, the system 100 cantrack and calculate a change in ambient temperature from the first timeto a second time. In response to the change in ambient temperature fromthe first time to the second time remaining below a low thresholdtemperature change, the system 100 can classify the fire event as anuisance fire. In response to the change in ambient temperature from thefirst time to the second time exceeding a high threshold temperaturechange, the system 100 can classify the fire event as a developing fire.Furthermore, in response to the change in ambient temperature from thefirst time to the second time remaining between the low thresholdtemperature change and the high threshold temperature change, the system100 can classify the fire event as an incipient fire.

Similarly, the system 100 can monitor a change in ambient humidityfollowing issuance of a fire event flag or confirmation of a fire event,and the system can assign a classification to the fire event as afunction of the rate of change in ambient humidity. In particular, as afire burns, ambient humidity may first increase and then decrease, asshown in FIGS. 1 and 4 , as the oxygen in the room is depleted; bytracking ambient humidity following issuance of a fire event flag orconfirmation of a fire event, the system 100 can detect this initialincrease and subsequent decrease in ambient humidity. In one example,after issuing a fire event flag or confirming the fire event at a firsttime, the system can: detect an increase in ambient humidity from thefirst time to a second time; detect a decrease in ambient humidity fromthe second time to a third time; and calculate a time difference betweenthe third time and the first time (e.g., a duration of time from whenambient humidity began to increase to a time that ambient humidity beganto decrease). If this time difference remains below a low time threshold(e.g., ambient humidity rapidly transitions from increasing todecreasing), the system 100 can classify the fire event as a developingfire. If this time difference exceeds the low time threshold and remainsbelow a high time threshold, the system 100 can classify the fire eventas an incipient fire. Furthermore, if this time difference exceeds thehigh time threshold (e.g., ambient humidity slowly transitions fromincreasing to decreasing), the system 100 can classify the fire event asa nuisance fire (or as representative of a change in an HVAC setting inthe building).

In the foregoing implementation, after issuing a fire event flag orconfirming a fire event in a room within a building, the system 100 can:monitor ambient humidity in the room and track increases and decreasesin ambient humidity while the fire continues to burn. In one example, inresponse to detecting a 10% increase in the ambient humidity followed bya 20% decrease in the ambient humidity within a two-minute period, thesystem 100 can classify the fire as an incipient fire. Also in thisexample, in response to detecting a 15% increase in the ambient humidityfollowed by a 30% decrease in the ambient humidity within a one-minuteperiod, the system 100 can classify the fire as a developing fire.Similarly, in response to detecting a 5% increase in the ambienthumidity followed by no or a minimum decrease in the ambient humiditywithin a three-minute period, the system 100 can classify the fire as anuisance fire.

As smoke from the fire reaches the system 100, the system 100 can alsodetect gaseous constituents of the smoke and map these constituents to afire classification. For example, because an incipient fire may burncleaner than both a smoldering fire and a developing fire, the system100 can map detected concentrations of CO and CO₂ below correspondingthreshold concentrations to an incipient fire, and the system 100 canmap concentrations of CO and CO₂ above corresponding thresholdconcentrations to either a smoldering fire or a developing fire, asshown in FIG. 2 .

Furthermore, as a fire burns within a space occupied by the system,smoke produced by the fire or light output by the fire itself can bedetected—by a motion sensor in the system 100—as motion. In one example,after issuing a fire event flag or confirming a fire event at a firsttime, the system 100 can detect a change in total motion level—from thefirst time to a second time—via the motion sensor. In response to thechange in motion level remaining below a low motion threshold, thesystem 100 can classify the fire event as a nuisance fire. In responseto the change in motion level exceeding the low motion threshold butremaining below a high motion threshold, the system 100 can classify thefire event as an incipient fire. Furthermore, in response to the changein motion level exceeding the high motion threshold, the system 100 canclassify the fire event as a developing fire. The system 100 can thusmonitor a fire event and classify the fire event as a function of motionlevel or changes in motion level over time.

As the fire continues to burn, the system 100 can repeat the foregoingmethods and techniques to reclassify the fire, such as the fire shiftsfrom an incipient fire to a developing fire or from an incipient fire toa smoldering fire.

8. Fire Composition

In one variation of the method S100, the system 100 also tracks ambientgas constituents and maps these ambient gas constituents to a safetyequipment callout for an emergency responder. In particular, the system100 can: detect a composition of gaseous combustion products within thespace in Block S134; and generate a protection equipment specificationfor the fire event based on the composition of gaseous combustionproducts in Block S152.

In another example, the system 100 can map a continuous rise in ambienttemperature and a magnitude of a fall in detected lightintensity—following a rise in ambient light intensity—to a density ofsmoke within the space; the system 100 can set an eye protection andoxygen supply callout for an emergency responder once the smoke densitypasses a threshold smoke density. However, in this example, if the smokedensity remains less than the threshold smoke density, the system 100can sample one or more internal gas sensors to determine the presence offlammable, noxious, or otherwise dangerous airborne compounds in thespace, such as propane, butane, or benzene. In response to detectedlevels of such compounds exceeding threshold levels, the system 100 cansimilarly set an oxygen supply callout for the emergency responder. Inthis example, the system 100 can also set a flag for a high-temperaturefire suit once the ambient temperature within the space rises above athreshold temperature.

In this variation, the system 100 can additionally or alternativelytransform detected ambient gas constituents into a possible fuel typebased on concentrations of various ambient gas constituents. Forexample, the system 100 can pass ambient gas constituent concentrationvalues into a lookup table to determine if the fuel source is wood,upholstery, paper, a liquid fuel (e.g., gasoline, paint thinner), etc.The system 100 can thus pass this determined fuel type to the emergencyresponder, as described below. Alternatively, based on the type of fuelsource associated with the ambient gas constituents and a value or rateof change in ambient temperature, humidity, light intensity,obscuration, motion, sound, etc., the system 100 can characterize a riskvalue for the fire event. For example, the system 100 (or the remotecomputer system receiving sensor data from the system 100 substantiallyin real-time) can classify the fire event as one of a green(“low-risk”), yellow (“moderate-risk”), or red (high-risk”) fire. Inanother example, the system 100 can rate the fire, such as on a scale of1-10 based on these factors. The system 100 can thus push these firerisk values to the emergency responder in Block S154, as describedbelow.

8.1 Fire Class

In this variation, in Block S160, the system 100 can assign a classdescriptor to a fire event based on characteristics of the fire (e.g.,based on sensor data collected at the system following confirmation ofthe fire event). The system 100 can then map the class descriptor of thefire event to a fire extinguishing equipment callout for an emergencyresponder. Generally, fires may be assigned different classes based onmaterials involved in ignition of the fire, such as: Class A firesstarted with combustible solids such as wood and paper; Class B firesstarted with flammable gases and liquids; Class C electrical firesinvolving potentially energized electrical equipment; Class D firesstarted with flammable metals; and Class K fires started with cookingfats or oils. Each class of fire may require a different type of fireextinguishing device to extinguish. For example, “water fireextinguishers” (i.e., fire extinguishers that dispense water toextinguish fires) may be commonly allocated to commercial andresidential buildings but may be suitable only for extinguishing Class Afires. In this example, water fire extinguishers may be dangerous foremergency responders when used on Class C electrical fires. Inparticular, water dispensed from a water fire extinguisher may conductelectricity from a Class C fire to an emergency responder, which mayresult in electrocution and/or death of the emergency responder. Inanother example, Class D (i.e., metal) fires may require dry powderextinguishing materials; and water dispensed from water fireextinguishers may excite Class D fires and cause Class D fires tospread.

In this variation, the system 100 can assign a class descriptor to afire event based on sensor data collected by the system 100 and knownparameter signatures (e.g., humidity, temperature, NOx gas, and/orcarbon dioxide signatures, etc.) of various classes of fires, such asdefined in a set of fire templates stored in local memory on the system100, as shown in FIG. 4 . For example, a Class D electrical fire mayproduce brighter light immediately followed by more smoke but initiallyburn at a lower temperature than a Class A fire. In another example, aClass A fire may exhibit a greater increase in ambient carbon dioxidethan a Class D metal fire.

In one implementation, the system 100 can access a database of firetemplates, wherein each fire template is associated with a differentfire class and defines a temporal relationship between variouscharacteristics of the fire and time, as shown in FIG. 4 . In responseto detecting and confirming a fire event, the system 100 can monitor andrecord the characteristics (e.g., temperature, humidity, lightintensity) of the fire over time through various integrated sensors asthe fire continues to burn. The system 100 can then compare developmentof (e.g., changes to) these characteristics of the fire over time tothese fire templates, match these characteristics to a particular firetemplate, and assign a class descriptor associated with the particularfire template to the fire event accordingly. After assigning the classdescriptor to the fire event, the system 100 can generate a fireextinguishing equipment callout specifying fire extinguishing equipmentrequired or expected to extinguish the fire based on the classdescriptor assigned to the fire event and then serve this fireextinguishing equipment callout to an emergency responder. Aftermatching the fire event to a fire template and assigning thecorresponding class descriptor to the fire event, the system 100 canalso predict future development of the fire in accordance with thematched fire template and past rates of change of various fireparameters (e.g., humidity, temperature, etc.). For example, the system100 can predict that the temperature of a Class C fire currently burningat 800° F. may increase until it reaches an ultimate temperature of1200° F. in eight minutes by mapping rates of change in ambient lightintensity, humidity, and temperature to the matched fire template. Inthis example, the system 100 can then transmit a notification to anemergency responder indicating that additional heat protection equipmentwill be required upon arrival at the burning building despite thecurrent temperature of the fire being only 800° F.

As shown in FIG. 6 , the system 100 can also generate a fireextinguishing callout based on the composition of gaseous combustionproducts. In particular, the system 100 can transform detected ambientgas constituents detected through sensors in the system 100 into apossible fuel type and correlate the possible fuel type with a fireclass, as described above. In this implementation, the system 100 can:determine a combustion source of a fire event based on a composition ofgaseous combustion products; generate a fire extinguishing specificationfor the fire event based on the combustion source of the fire; andtransmit the fire extinguishing specification to an emergency responder,as described below. For example, if the system 100 detects trace amountsof magnesium in the gaseous combustion products of a fire event, thesystem 100 can determine that the fire event is a Class D metal fire andthen notify an emergency responder that the fire event requires a drypowder fire extinguisher. Similarly, if the system 100 detects traceamounts of copper in the gaseous combustion products of a fire event,the system 100 can determine that the fire event is a Class C electricalfire.

9. Fire Modeling

In one implementation, the system 100 implements one or more decisiontrees to confirm a fire event, to determine a fire classification forthe confirmed fire event, to generate a protection equipmentspecification for the fire event, and/or to assess a risk value for thefire event, such as shown in FIGS. 2 and 5 .

In another implementation, the system 100 can implement non-parametrictechniques, such as template matching, to transform sensor datacollected from one or more internal sensors over time into confirmationof a fire event, classification of the fire event, a protectionequipment specification, and/or a risk value assessment for the fireevent, as shown in FIG. 4 . For example, for each sensor channelsupported by the system 100, the system 100 can store—in local memory—aset of time-dependent data templates (e.g., images, charts) for each ofvarious fire classifications across various fire sizes, fuel sources,etc. In this example, for the system 100 that includes [a light sensor,an humidity sensor, a temperature sensor, a CO sensor, a CO₂ sensor, anoxygen sensor, a volatile gas sensor, and a motion sensor], the system100 can store time-dependent [light intensity, humidity, temperature,CO, CO₂, oxygen, volatile gas, and motion] templates for the duration ofeach of [an incipient fire, a developing fire, and a smoldering fire] of[small, medium, and large] sizes (e.g., 50 kW, 500 kw, 5 MW power,respectively) for each of a [paper, wood, gas or oil, andupholstery]-type primary fuel source. Therefore, in this example, thesystem 100 can store 288 time-dependent data templates covering eightsensor channels across 72 characterized fires. For each internal sensorwithin the system 100, the system 100 can match time-dependent dataoutput by the sensor—such as starting at a detected or confirmed fireevent—to a time-dependent data template for the sensor type. Based on anumber of sensor data streams that match time-dependent data templatesfor a template fire, the system 100 can calculate a confidence intervalfor a template-based classification for a detected fire. The system 100can also calculate a confidence interval for a template-basedclassification for a detected fire based on a degree of overlap betweensensor data streams and time-dependent data templates. Furthermore, whenmatching a time-based data stream from a sensor, the system 100 canstretch or compress the data stream in real time in order to fit thesensor stream to a data template for the sensor, and the system 100 canestimate a trajectory or rate of growth of the fire based on a stretchor compression coefficient thus applied to the data stream. The system100 can similarly stretch or compress a data stream from a sensor alonga sensed value axis in order to fit the sensor stream to a data templatefor the sensor, and the system 100 can estimate a size of the fire basedon a stretch or compression coefficient thus applied to the data stream.However, the system 100 can implement any other template matchingtechnique to match sensor data to a corresponding data template toconfirm and/or classify a fire.

In another implementation, the system 100 can implement a parametricmodel—stored locally in memory in the system 100—to detect, confirm,classify, and/or monitor a fire. For example, the system 100 canimplement a parametric model that outputs a fire classification and afire severity value as a function of: time (t) from detection of apossible fire event (or time from a confirmed fire event) (to); changesin humidity, temperature, air composition (e.g., ppm CO₂, ppm benzene),and/or light intensity, etc. since to; and/or rates of change inhumidity, temperature, air composition, and/or light intensity, etc.over limited time durations (e.g., a past set of four sampling periods);etc. The system 100 can therefore implement a parametric model thattransforms changes (and rates of change) in values output by one or moresensors within the system 100 over time into a quantitative and/or aqualitative value representative of the current state of a detectedfire.

In the foregoing implementation, a remote computer system: can collectsensor data from similar systems deployed to various spaces; and canthen implement (semi-) supervised machine learning techniques togenerate the parametric model based on these sensor data andhuman-supplied feedback pertaining to environment, severity and/orclassification of fires measured by these similar systems. Theparametric model can be pre-loaded onto the system 100 during itsmanufacture or can be uploaded to the system 100—such as via theInternet—when the system 100 is installed. The remote computer systemcan also collect such sensor data from these deployed systems, retrievefire data supplied by humans (e.g., emergency responders) for firesburning near these deployed system, and refine the parametric modelbased on these sensor data and human feedback data. The remote computersystem can thus continue to refine the parametric model based onadditional fire-related data collected from like deployed systems overtime and can automatically push updated parametric models to new andremaining systems in deployment. (In the previous implementation, thesystem 100 can implement similar techniques to generate and/or refinedata templates for sense channels supported by the system 100 based onadditional data collected from deployed systems over time and to pushnew or refined data templates to systems remaining in deployment.)

However, the system 100 can implement any other method or technique totransform data collected from various sensors within the system 100 intodetection of a fire, confirmation of a fire, classification of a fire,etc.

In one variation, the system 100 implements a decision tree, datatemplates, and/or a parametric model based on the installationconfiguration of the system 100. For example, when an installer installsthe system 100 in a space, the installer can indicate whether the system100 is installed on a wall or on a ceiling through native system setupapplication, as described above; the remote computer system can select awall-specific or ceiling-specific decision tree (or set of datatemplates, parametric model) for the system 100 accordingly and thenautomatically push the selected decision tree to the system 100. In thisexample, the installer can also indicate: whether the system 100 isinstalled on a wall or on a ceiling; whether the system 100 is installedin the center of the ceiling or in a corner of the ceiling of a space; asize (e.g., length, width, ceiling height) of the space; and/or a commonconstruction material within a space (e.g., wood, concrete, sheetrock,wool carpet); etc., and the remote computer system can select a decisiontree (or set of data templates, parametric model) specific to acombination of one or more of the foregoing installation parameters andthe installation configuration of the system 100. In a similar example,the system 100 can include a tilt sensor or an accelerometer, candetermine its installation orientation based on an output of the tiltsensor or accelerometer, and can automatically retrieve a decision tree(or set of data templates, parametric model) specific to itsinstallation configuration. However, the system 100 and/or the remotecomputer system can select a particular decision tree, set of datatemplates, or parametric model for the system 100 based on any other oneor more installation parameters.

10. Alarms and Communications

Generally, in Block S150, the system 100 functions to transmit an alarmto an emergency responder in response to confirmation of a fire event.For example, in response to confirmation of a fire, the system 100 canupload a fire alarm directly to an emergency responder dispatch or to aremote computer system that distributes a fire alarm to an emergencyresponder dispatch. In this example, the system 100 can transmit firealarm data over short- or medium-range wireless communication protocol,such as over Wi-Fi, or over long-range wireless communication protocol,such as over a cellular connection. When a detected fire is confirmed,the system 100 can also broadcast a fire alarm to an alarm systemintegrated into the space in which the system 100 is installed, and theintegrated alarm system can issue an audible and/or visual alarm withinthe space.

In one implementation, the system 100 transmits a communication ornotification of a fire event to an occupant of the building, to abuilding operator or engineer in the building, or to an emergencyresponder during and/or after a fire event, such as through an operatorportal executing on or accessible through a desktop or mobile computingdevice. The system 100 can also transmit notifications of differenttypes to various stakeholders affiliated with the building at differenttimes throughout the duration of a fire event. For example, the system100 can: transmit a first notification indicating possibility of fire toa building operator (e.g., to an engineering portal executing on adesktop computer within the building) after setting a fire event flag ata first time; transmit a second notification indicating confirmation ofthe fire event to the building operator and to an emergency responder(e.g., to a dispatcher portal executing on a desktop computing device atan emergency dispatcher) in response to confirming the fire event flagat a second time based on data collected following the first time; andthen transmit a third notification indicating a fire classification tothe emergency responder after classifying the fire event at a third timebased on data collected following the second time. In this example, thesystem 100 can also: transmit a fire alarm to a building operator toprompt the building operator to immediately contain and extinguish afire in response to classifying a fire event as an incipient fire;transmit a fire alarm to an emergency responder prompting response to afire at the building and transmit a notification to evacuate thebuilding to the building operator and/or other occupants of the buildingin response to classifying the fire event as a developing fire; ordiscard a fire event in response to classifying the fire event as anuisance fire and then serve an audible notification through an audiosystem arranged in the building to extinguish the nuisance fire.

The system 100 can also transmit a communication or notification to anoccupant, building operator, or emergency responder in response todetecting a change in ambient conditions within a room of a buildingand/or in response to detecting a change in fire classification of adetected fire in the building. In this implementation, the system 100can: set a fire event flag at a first time; detect a first change inambient temperature—via a temperature sensor in the system 100—from thefirst time to a second time; confirm the fire event flag as a fire eventif the first change in ambient temperature exceeds a thresholdtemperature change; and then transmit a fire alarm to an emergencyresponder. In this implementation, the system 100 can also: detect anincrease in ambient temperature—via the temperature sensor—to a thirdambient temperature at a third time; and transmit a specification foradditional heat protection to the emergency responder in response to thethird ambient temperature exceeding a threshold ambient temperature. Forexample, after confirming a fire event based on an increase in ambienttemperature from 72° F. to 81° F. over a period of two minutes, thesystem 100 can transmit a fire alarm to an emergency responder; if thesystem 100 subsequently detects an increase in ambient temperaturegreater than 169° F. (e.g., to a threshold ambient temperature of 250°F.), the system 100 can transmit a second communication to the emergencyresponder recommending additional heat protection equipment.

During a fire event, the system 100 can also correlate a decrease inlight intensity with an increase in density of smoke near a lightdetector. In response to the calculated or estimated density of smokeexceeding a threshold smoke density, the system 100 can also transmit aspecification for secondary oxygen supply to the emergency responder.The system 100 can thus monitor the fire event as the fire continues toburn and notify emergency responders when specific or additionalprotection or extinguishing equipment is required as a function ofdetected characteristics of the fire over the course of the fire event.

In one implementation, the system 100 selectively delays transmission ofa fire alarm to an emergency responder based on a classification of thefire (and/or based on a detected size of the fire or rate of change ofthe fire). For example, the system 100 can automatically transmit a firealarm to an emergency responder for fires characterized as developingand smoldering but can delay transmission of a fire alarm to anemergency responder for a limited period of time (e.g., 30 seconds) fora confirmed fire characterized as incipient. In this example, inresponse to confirmation of a fire, the system 100 can: automaticallyactuate a first audible siren at a first sound level; in response toconfirmation of the fire as incipient, set a time for 30 seconds andmaintain the first audible alarm; and, if the fire persists or is largerin size (e.g., if the light sensor detects the same or greater level oflight intensity) at the expiration of the timer, actuate a secondaudible siren at a higher sound level and push a fire alarm to a remoteresponder. Furthermore, the system can set a delay time—betweenconfirmation of a fire event and transmission of a fire alarm to anemergency responder—dynamically based on size and/or a rate of increasein fire intensity for an incipient fire. Therefore, for an incipientfire, the system 100 can audibly notify a person within the space of thefire with a lower-volume siren to permit the person to extinguish theincipient fire; if the fire is not extinguished or handled within alimited period of time, the system 100 can then automatically notify anemergency responder and issue a siren at a higher volume to ensure thatpersons within the space are notified of and leave the fire.

In the implementation described above in which the system 100 continuesto monitor a fire after confirmation and transmission of a fire alarm toan emergency responder, the system 100 can also transmit fireclassification, size, intensity, temperature, location, and/or otherfire-related data to an emergency responder while a fire burns near thesystem 100. For example, the system 100 can stream both humidity, lightintensity, temperature, and/or other raw sensor data and fireclassifications to an emergency responder over a cellular or Wi-Ficonnection. In another example, the system 100 can limit transmission offire-related data to significant changes in the state of the fire, suchas a change in the classification of the fire, a threshold change in therisk level of the fire on a risk scale, or a change in a protectionequipment specification (e.g., due to detected changes in temperature orgas constituents within the space), etc. However, the system 100 canpush any other type of raw or processed data to the emergency responder(or emergency responder dispatch, remote computer system, etc.) in anyother frequency or according to any other communication schema.

The system 100 can additionally or alternatively upload raw sensor datato the remote computer system (e.g., a remote server), and the remotecomputer system can implement the foregoing methods and techniques todetect, confirm, classify, and/or monitor a fire event and to transmit afire alarm and/or fire-related data to an emergency responder.

10. Virtual Map

As shown in FIG. 7 , one variation of the method S100 includes BlockS110, which recites: generating a virtual map for a fire event,populating the virtual map with information pertaining to the fireevent; transmitting the virtual map to an emergency responder; updatingthe virtual map as new information pertaining to the fire event isreceived; and transmitting an updated version of the virtual map to theemergency responder. Generally, in Block S110, the system 100 (or aremote computer system, such as a central controller within the buildingor a remote server in communication with the system 100 can generate agraphical representation (e.g., a virtual map) of the structure and afire event detected within the structure; the system 100 can then servethe graphical representation to an emergency responder in order toassist the emergency responder in planning for and eventually respondingto the fire event.

In one implementation, the system 100: accesses a digital floor plan(e.g., two-dimensional or three-dimensional engineering plan) of thebuilding and a lookup table linking UUIDs of deployed units of thesystem 100 (and/or other sensing devices within the building, asdescribed below) to specific rooms, areas, or volumes within thebuilding; and then inserts (near) real-time information collected bythese deployed units of the system 100 (and/or by other sensing devices)into a graphical representation of the floor plan to create a “virtualmap” representing the current state of the building and one or more fireevents detected within the building. The system 100 can then transmitthe virtual map to a building operator or to an emergency responder in(near) real-time such as through building operator and emergencyresponder portals executing on corresponding computing devices.

Therefore, in this implementation, the system can generate a virtual mapconfigured to assist a building operator or emergency responder inquickly ascertaining the current location, size, class, and/or state(and predicted future state) of one or more fire events within thebuilding, thereby enabling the building operator or emergency responderto systematically address the fire event. For example, the system canpopulate the virtual map with visual representations of: fire events invarious rooms throughout the building; a directionality of each fireevent within the building; a classification of each fire event (e.g.,nuisance, incipient, or developing) detected in each room of thebuilding; a fire class of each fire event (e.g., Class A, B, C, D, orK); a composition of gaseous combustion products detected near each fireevent in the building; a fire extinguishing equipment callout for eachfire event; an ambient temperature in each room or area within thebuilding; and/or a protection equipment specification for each fireevent, etc.

In Block S172, the system 100 can assign a color to each fireclassification, fire class, ambient temperature range, etc. and colorareas of the virtual map or specific fire events within the virtual mapwith a representative color, as shown in FIG. 7 . An emergency respondermay thus ascertain a fire classification, fire class, and/or ambienttemperature etc. of fires or volumes throughout the building based oncolors of areas throughout the virtual map; the emergency responder canthus quickly identify and prioritize areas within the building requiringa most rapid response based on such data contained in the virtual map.

In this variation, a local controller or remote computer system can:generate or receive a fire event and a fire classification from a unitof the system 100 arranged within a structure; access a virtual map ofthe structure defining a known location of the unit of the system 100;label the known location of the unit within the virtual map with thefire event and the fire classification received from the fire detector;and transmit the virtual map to an emergency responder. For example,after detecting and confirming a fire event within a building, the localcontroller or remote computer system can: classify the fire event as adeveloping fire; populate a virtual map of the building with thelocation of the fire event and an indicator of a developing fire; andthen transmit the virtual map—indicating the location and developingfire classification of the fire event—to an emergency responder drivingto the building. The emergency responder may then use this informationto develop a strategy for fighting the fire while in transit to thebuilding.

In Block S174, the system 100 can regularly update the virtual map ofthe building throughout the fire event. For example, during the fireevent, as the fire continues to burn, the status of the fire (e.g., itstemperature, rate of growth, size, direction or spread, classification,and/or class, etc.) may change. The system 100 (or a local controller orremote computer system in communication with units of the systemdeployed throughout the building) can therefore update the virtual mapwith various raw or processed data pertaining to the fire event andtransmit updated variants of the virtual map to a building operator,emergency responder, or other stakeholder throughout the fire event,such as on a regular interval of 1 Hz or once per 30-second interval.The system 100 (or the local controller or remote computer system incommunication with units of the system deployed throughout the building)can therefore provide the building operator, emergency responder, orother stakeholder with a (near) real-time view of various statisticsrelated to fire events within the building, which may aid thesestakeholders in responding to and managing these fire events. Forexample, the local controller or remote computer system can regularly:receive a temperature value from a unit of the system 100 arranged inthe building; label a known location of the unit within the virtual mapwith the temperature value received from the unit; and transmit thevirtual map to an emergency responder in near real-time during the fireevent.

The local controller or remote computer system can also populate thevirtual map with a prediction of how a fire event may develop in thefuture. In this implementation, the system 100 can predict future statesor characteristics of a fire event based on past data collected fromunits of the system deployed in the building. For example, afterdetermining that a fire event detected by a unit of the system 100 is adeveloping, Class A fire, the local controller or remote computer systemcan predict—based on the developing fire classification and the Class Afire descriptor—that the fire event will likely increase in temperatureuntil it reaches an ultimate ambient temperature of 1200° F. The system100 can then transmit a notification to an emergency responderindicating that heat protection equipment necessary for a 1200° F. maybe required. The system 100 can then depict the predicted ultimatetemperature on the virtual map in the vicinity of the fire event. Thelocal controller or remote computer system can similarly predict afuture state of the fire event based on a fire template matched tofire-related data collected by a unit of the system 100, as describedabove. In another example, the local controller or remote computersystem can: predict a future location and size of the fire event basedon a direction of the fire event extrapolated from data collected overtime through multiple units of the system 100 deployed throughout thebuilding; and then insert these predictions into a virtual map served tothe emergency responder.

9. Distributed Sensors

In one variation, the system 100 can be implemented at a building (e.g.,a commercial or residential structure) with previously-installed sensingdevices. For example, rooms and spaces within a commercial building mayinclude: traditional fire detectors capable of detecting fire eventsbased on presence of smoke; thermometers and humidity sensors connectedto a central heating, ventilation, and air conditioning (or “HVAC”)system in the building; and/or motion detectors (e.g., light-basedmotion detectors) connected to an occupant management and lightingsystem within the building. In this variation, Blocks of the method S100can be executed by a local controller within the building or by a remotecomputer system to leverage these sensing devices to collect light,temperature, humidity, motion and/or data previously installedthroughout the building. The local controller or remote computer systemcan thus routinely monitor rooms or spaces within the building for fireevents based on these data streams imported from distributed sensorsconnected to one or multiple discrete sensor networks throughout thebuilding. For example, in this variation, the local controller can beintegrated into a building management system or a building automationsystem configured to monitors and control a building's mechanical,electrical, HVAC, and/or other equipment.

In one example, when executing the method S100, the local controller orremote computer system can interpret: an increase in light intensitydetected by a motion sensor arranged in a room of the building andconnected to a lighting system in the building; followed by an increasein temperature detected (in the same or nearby room or space) by apreviously-installed thermometer connected to an HVAC system within thebuilding as a possible fire event and issue a fire event flagaccordingly. The local controller or remote computer system can thentransmit a notification to a building operator indicating a possiblefire event, as described above. In this example, the local controller orremote computer system can continue to monitor changes in humiditywithin or near this room or space through a previously-installedhumidity sensor connected to the building's HVAC system. In response todetecting an increase in humidity, the local controller or remotecomputer system can transmit a notification to the building operatorconfirming the fire event, as described above.

In this variation, the local controller or remote computer system canaccess data from previously-installed sensing devices within thebuilding via a wired or wireless network. The local controller or remotecomputer system can also identify a type of the sensing device (e.g., afire detector, an HVAC sensor block, etc.), a type of sensor included ineach sensing device (e.g., a temperature sensor, a light sensor, amoisture or humidity sensor, etc.), and/or a location of the sensingdevice within the building, such as based on identifiers (e.g., a UUIDs)contained in data packets received from each sensing device. The localcontroller or remote computer system can also: access a digital floorplan of the building; locate these previously-installed sensing deviceswithin the digital floor plan; map types of sensing device, types ofsensors integrated into each sensing device, and/or data streamsreceived from these sensing devices to corresponding regions of thedigital floor plan, such as based on a lookup table or name mappingsystem, to generate a virtual map of the building containing real-timestatistics of rooms and spaces within the building.

The systems and methods described herein can be embodied and/orimplemented at least in part as a machine configured to receive acomputer-readable medium storing computer-readable instructions. Theinstructions can be executed by computer-executable componentsintegrated with the application, applet, host, server, network, website,communication service, communication interface,hardware/firmware/software elements of a user computer or mobile device,wristband, smartphone, or any suitable combination thereof. Othersystems and methods of the embodiment can be embodied and/or implementedat least in part as a machine configured to receive a computer-readablemedium storing computer-readable instructions. The instructions can beexecuted by computer-executable components integrated bycomputer-executable components integrated with apparatuses and networksof the type described above. The computer-readable medium can be storedon any suitable computer readable media such as RAMs, ROMs, flashmemory, EEPROMs, optical devices (CD or DVD), hard drives, floppydrives, or any suitable device. The computer-executable component can bea processor but any suitable dedicated hardware device can(alternatively or additionally) execute the instructions.

As a person skilled in the art will recognize from the previous detaileddescription and from the figures and claims, modifications and changescan be made to the embodiments of the invention without departing fromthe scope of this invention as defined in the following claims.

I claim:
 1. A method for detecting a fire comprising: accessing adigital floor plan of a structure; associating a first sensing device toa first room within the structure; accessing a first fire event for thefirst room, a first fire classification for the first fire event, and afirst ambient temperature in the first room from the first sensing unit;at a first time, interpolating real-time information collected by thefirst sensing device into a graphical representation of the floor planto generate a first virtual map; populating the first virtual map withvisual representations of the first fire event, the first classificationfor the first fire event, and the first ambient temperature;transmitting the first virtual map to a responder portal; between thefirst time and a second time, in response to an increase detected forthe first ambient temperature: updating the first ambient temperature toa second ambient temperature; and updating the first fire classificationto a second fire classification; at the second time, updating the firstvirtual map to a second virtual map; populating the second virtual mapwith visual representations of the first fire event, the secondclassification for the first fire event, and the second ambienttemperature; and transmitting the second virtual map to the responderportal.
 2. The method of claim 1, further comprising: over a firstperiod of time preceding the first time, detecting a first increase inambient humidity via a humidity sensor; over the first period of timepreceding the first time, detecting a first increase in ambienttemperature via a temperature sensor arranged proximal the humiditysensor; and in response to the first increase change in ambienttemperature exceeding a threshold temperature change and the firstincrease in ambient humidity exceeding a threshold humidity change:interpreting the first increase in ambient temperature and the firstincrease in ambient humidity as the first fire event; and transmitting afire alarm for the first fire event to the responder portal of anemergency responder.
 3. The method of claim 2, further comprising: overthe first period of time preceding the first time: recording a sequenceof ambient light intensities via a light sensor; recording a sequence ofambient temperature values via the temperature sensor; and recording asequence of ambient humidity values via the humidity sensor; and inresponse to interpreting the first increase in ambient temperature andthe first increase in ambient humidity as the first fire event:selecting a time-dependent fire data template, from a set oftime-dependent fire data templates, analogous to the fire event based oncorrelations between the sequence of ambient light intensities, thesequence of ambient temperature values, the sequence of ambient humidityand light intensity, temperature, and humidity data stored in thetime-dependent fire data template; generating the first fireclassification of the first fire event based on the time-dependent firedata template, the classification indicating a combustion source of thefirst fire event; and transmitting a fire extinguishing specificationand a first protective equipment specification to the responder portalbased on the first fire classification of the fire event.
 4. The methodof claim 3, further comprising: calculating a set of time coefficientsbetween: the sequence of ambient light intensities, the sequence ofambient temperature values, the sequence of ambient humidity values; andlight intensity, temperature, and humidity data stored in thetime-dependent fire data template; predicting a rate of growth of thefirst fire event based on a set of compression coefficients; andtransmitting the predicted rate of growth of the first fire event to theresponder portal.
 5. The method of claim 3, further comprising: atapproximately the first time, calculating a first risk level for thefire event based on the sequence of ambient light intensities, thesequence of ambient temperature values, and the first fireclassification of the first fire event; at the second time succeedingthe first time, calculating a second risk level for the first fire eventbased on the sequence of ambient light intensities, the sequence ofambient temperature values, and the second fire classification of thefirst fire event; in response to the second risk level exceeding thefirst risk level by a threshold change in risk level, reporting thesecond risk level to the responder portal; and in response toincompatibility between the first protective equipment specification andthe second risk level: generating a second protective equipmentspecification corresponding to the second risk level; and transmittingthe second protective equipment specification to the responder portal.6. The method of claim 1, further comprising: in response to theincrease detected for the first ambient temperature between the firsttime and the second time: predicting a direction of spread of the firethroughout the structure based on relative locations of the first roomand a second room; and predicting a rate of growth of the fire withinthe structure based on an elapsed time between the first time and thesecond time; and indicating the predicted direction of spread of thefire and the predicted rate of growth of the fire on the second virtualmap.
 7. The method of claim 1, further comprising: at a gas sensor inthe first room, detecting a composition of gaseous combustion productswithin the space; predicting a combustion source of the first fire eventbased on the composition of gaseous products; generating a first fireextinguishing specification based on the combustion source of the firstfire event; and transmitting the first fire extinguishing specificationto the responder portal.
 8. The method of claim 1, further comprising:annotating the representation of the first fire event with a firsttemperature value measured, at a third time, by the first sensingdevice; annotating a representation of a second fire event with a secondtemperature value measured, at the third time, by a second sensingdevice deployed in a second room in a set of the rooms of the structure;generating a specification for additional heat protection equipmentbased on the first temperature value and the second temperature value;updating the second virtual map to a third virtual map to reflect thefirst temperature value in the first room and to reflect the secondtemperature value in the second room; and transmitting the specificationfor additional heat protection equipment to the responder portal.
 9. Themethod of claim 8, further comprising: at a first gas sensor within thefirst sensing device, detecting a first composition of gaseouscombustion products within the first room; at a second gas sensor withinthe second sensing device, detecting a second composition of gaseouscombustion products within the second room; generating a protectiveequipment specification for the first fire event and the second fireevent based on the first composition of gaseous combustion products andthe second composition of gaseous combustion products; and transmittingthe protective equipment specification to the responder portal.
 10. Amethod for detecting a fire comprising: accessing a digital floor planof a structure; associating a first sensing device to a first roomwithin the structure; associating a second sensing device to a secondroom within the structure; accessing a first fire event for the firstroom, a first fire classification for the first fire event, and a firstambient temperature in the first room from the first sensing unit; at afirst time, interpolating real-time information collected by the firstsensing device into a graphical representation of the floor plan togenerate a first virtual map; populating the first virtual map withvisual representations of the first fire event, the first classificationfor the first fire event, and the first ambient temperature;transmitting the first virtual map to a responder portal; between thefirst time and a second time, in response to a second fire eventdetected for the second room: accessing a second fire classification forthe second fire event; and accessing a second ambient temperate for thesecond room; at the second time, updating the first virtual map to asecond virtual map; populating the second virtual map with visualrepresentations of the second fire event, the second classification forthe second fire event, and the second ambient temperature; andtransmitting the second virtual map to the responder portal.
 11. Themethod of claim 10, further comprising: over a first period of timepreceding the first time, detecting a first increase in ambient humidityfor the first room via a humidity sensor; over the first period of timepreceding the first time, detecting a first increase in the firstambient temperature for the first room via a temperature sensor arrangedproximal the humidity sensor; and in response to the first increasechange in ambient temperature for the first room exceeding a thresholdtemperature change and the first increase in ambient humidity for thefirst room exceeding a threshold humidity change: interpreting the firstincrease in ambient temperature and the first increase in ambienthumidity as the first fire event; and transmitting a fire alarm for thefirst fire event to the responder portal of an emergency responder. 12.The method of claim 11, further comprising: in response to interpretingthe first increase in ambient temperature and the first increase inambient humidity as the first fire event within the first room:predicting a direction of spread of the fire throughout the structurebased on relative locations of the first room and the second room; andpredicting a rate of growth of the fire within the structure based on anelapsed time between the first time and the second time; and indicatingthe predicted direction of spread of the fire and the predicted rate ofgrowth of the fire on the second virtual map.
 13. The method of claim11, further comprising: detecting a second increase in ambienttemperature at the temperature sensor from a second time periodsucceeding the first time; and in response to the second increase inambient temperature exceeding a second threshold ambient temperaturechange, transmitting a specification for additional heat protection tothe responder portal.
 14. The method of claim 11, further comprising:over the first period of time preceding the first time: recording asequence of ambient light intensities via a light sensor in the firstroom; recording a sequence of ambient temperature values via thetemperature sensor; and recording a sequence of ambient humidity valuesvia the humidity sensor; and in response to interpreting the firstincrease in ambient temperature and the first increase in ambienthumidity as the first fire event: selecting a time-dependent fire datatemplate, from a set of time-dependent fire data templates, analogous tothe fire event based on correlations between the sequence of ambientlight intensities, the sequence of ambient temperature values, thesequence of ambient humidity and light intensity, temperature, andhumidity data stored in the time-dependent fire data template;generating the first fire classification of the first fire event basedon the time-dependent fire data template, the classification indicatinga combustion source of the first fire event; and transmitting a fireextinguishing specification and a first protective equipmentspecification to the responder portal based on the first fireclassification of the fire event.
 15. The method of claim 14, furthercomprising: calculating a set of time coefficients between: the sequenceof ambient light intensities, the sequence of ambient temperaturevalues, the sequence of ambient humidity values; and light intensity,temperature, and humidity data stored in the time-dependent fire datatemplate; predicting a rate of growth of the first fire event based on aset of compression coefficients; and transmitting the predicted rate ofgrowth of the first fire event to the responder portal.
 16. The methodof claim 14, further comprising: at approximately the first time,calculating a first risk level for the fire event based on the sequenceof ambient light intensities, the sequence of ambient temperaturevalues, and the first fire classification of the first fire event; atthe second time succeeding the first time, calculating a second risklevel for the second fire event based on sequence of ambient lightintensities, sequence of ambient temperature values, and the second fireclassification of the second fire event; in response to the second risklevel exceeding the first risk level by a threshold change in risklevel, reporting the second risk level to the responder portal; and inresponse to incompatibility between the first protective equipmentspecification and the second risk level: generating a second protectiveequipment specification corresponding to the second risk level; andtransmitting the second protective equipment specification to theresponder portal.
 17. The method of claim 10, further comprising: at agas sensor in the first room, detecting a composition of gaseouscombustion products within the first room; predicting a combustionsource of the first fire event based on the composition of gaseousproducts; generating a first fire extinguishing specification based onthe combustion source of the first fire event; and transmitting thefirst fire extinguishing specification to the responder portal.
 18. Themethod of claim 10, further comprising: at a first gas sensor within thefirst sensing device, detecting a first composition of gaseouscombustion products within the first room; at a second gas sensor withinthe second sensing device, detecting a second composition of gaseouscombustion products within the second room; generating a protectiveequipment specification for the first fire event and the second fireevent based on the first composition of gaseous combustion products andthe second composition of gaseous combustion products; and transmittingthe protective equipment specification to the responder portal.
 19. Amethod for detecting a fire comprising: accessing a digital floor planof a structure; associating a first sensing device to a first roomwithin the structure; accessing a first fire event for the first room, afirst fire classification for the first fire event, and a first ambienttemperature in the first room from the first sensing unit; at a firsttime, interpolating real-time information collected by the first sensingdevice into a graphical representation of the floor plan to generate afirst virtual map; populating the first virtual map with visualrepresentations of the first fire event, the first classification forthe first fire event, and the first ambient temperature; transmittingthe first virtual map to a responder portal; between the first time anda second time, in response to an increase detected for the first ambienttemperature: predicting a direction of spread of the fire throughout thestructure based on relative locations of the first room and a secondroom; predicting a rate of growth of the fire within the structure basedon an elapsed time between the first time and the second time; at thesecond time, updating the first virtual map to a second virtual map;populating the second virtual map with visual representations of thepredicted direction of spread of the fire, and the predicted rate ofgrowth of the fire; and transmitting the second virtual map to theresponder portal.
 20. The method of claim 19, further comprising: over afirst period of time preceding the first time, detecting a firstincrease in ambient humidity via a humidity sensor; over the firstperiod of time preceding the first time, detecting a first increase inambient temperature via a temperature sensor arranged proximal thehumidity sensor; and in response to the first increase change in ambienttemperature exceeding a threshold temperature change and the firstincrease in ambient humidity exceeding a threshold humidity change:interpreting the first increase in ambient temperature and the firstincrease in ambient humidity as the first fire event; and transmitting afire alarm for the first fire event to the responder portal of anemergency responder.